Ai, Statistics & Data Science in Practice Webinar - April 21, 2026

Tuesday, April 21, 2026 - 12:00pm to 1:30pm ET

Speaker

Anastasios N Angelopoulos, UC Berkeley

Moderator

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Zoom Registration Coming Soon!

Overview

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About the Speaker

Anastasios Nikolas Angelopoulos is a sixth-year Ph.D. student at the University of California, Berkeley, advised by Michael I. Jordan and Jitendra Malik. From 2016 to 2019, he was an electrical engineering student at Stanford University advised by Gordon Wetzstein and Stephen P. Boyd. His research interests include Theoretical statistics + black-box machine learning models. How can we do statistics with ML in the loop, and no assumptions on the model at all? I'm especially interested in simple, easy-to-use algorithms with formal mathematical validity guarantees. Much of my work has centered around conformal prediction and prediction-powered inference. He also has a research interest in evaluations, and seeks to measure how we effectively test and evaluate models to make sure they are safe and performant. He helped build the leading online platform for evaluating Large Language Models, Chatbot Arena. He has also thought about methods for autoevaluation: using synthetic data for efficient and cost-effective evaluation. His other research interests include computer vision, computational imaging, biomedicine. His research career began in imaging and clinical medicine, and these are still his greatest motivations. He seeks to build computational and statistical systems that change the way we understand the human body and treat diseases. End-to-end approaches involving automatic vision-based reconstruction, recognition, and decision-making often excite me most. At Berkeley, he was the recipient of the Leon O. Chua Department Award. He was supported by a National Science Foundation Graduate Research Fellowship and a Berkeley Fellowship. He is also a Sequoia Open Source Software Fellow. At Stanford, he was a National Merit Scholar and received the Terman Award, Phi Beta Kappa, Tau Beta Pi, and departmental distinction. See Profile

 

About the Moderator

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About AI, StAtIstics and Data Science in Practice 

The NISS AI, Statistics and Data Science in Practice is a monthly event series will bring together leading experts from industry and academia to discuss the latest advances and practical applications in AI, data science, and statistics. Each session will feature a keynote presentation on cutting-edge topics, where attendees can engage with speakers on the challenges and opportunities in applying these technologies in real-world scenarios. This series is intended for professionals, researchers, and students interested in the intersection of AI, data science, and statistics, offering insights into how these fields are shaping various industries. The series is designed to provide participants with exposure to and understanding of how modern data analytic methods are being applied in real-world scenarios across various industries, offering both theoretical insights, practical examples, and discussion of issues.

Featured Topics:

Event Type

  • NISS Hosted

Cost

Free Webinar

Location

Free Zoom Webinar
United States

Policy